自然语言生成综述

自然语言生成（NLG）技术利用人工智能和语言学的方法来自动地生成可理解的自然语言文本。NLG降低了人类和计算机之间沟通的难度，被广泛应用于机器新闻写作、聊天机器人等领域，已经成为人工智能的研究热点之一。首先，列举了当前主流的NLG的方法和模型，并详细对比了这些方法和模型的优缺点；然后，分别针对文本到文本、数据到文本和图像到文本等三种NLG技术，总结并分析了应用领域、存在的问题和当前的研究进展；进而，阐述了上述生成技术的常用评价方法及其适用范围；最后，给出了当前NLG技术的发展趋势和研究难点。

Summarization of natural language generation

Natural Language Generation (NLG) technologies use artificial intelligence and linguistic methods to automatically generate understandable natural language texts. The difficulty of communication between human and computer is reduced by NLG, which is widely used in machine news writing, chatbot and other fields, and has become one of the research hotspots of artificial intelligence. Firstly, the current mainstream methods and models of NLG were listed, and the advantages and disadvantages of these methods and models were compared in detail. Then, aiming at three NLG technologies:text-to-text, data-to-text and image-to-text, the application fields, existing problems and current research progresses were summarized and analyzed respectively. Furthermore, the common evaluation methods and their application scopes of the above generation technologies were described. Finally, the development trends and research difficulties of NLG technologies were given.